Evidence map›Paper›PMID 38585727›Full record

ArticlebioRxiv : the preprint server for biology2024

Taxonize-gb: A tool for filtering GenBank non-redundant databases based on taxonomy.

Mohamed S Sarhan, Michele Filosi, Frank Maixner, Christian Fuchsberger

Abstract readPreprint
In one paragraph

Article in bioRxiv : the preprint server for biology, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

4 authors.

Mohamed S SarhanInstitute for Biomedicine, Eurac Research, Bolzano 39100, Italy (Affiliated institute with Lübeck University, Lübeck, Germany).ORCID 0000-0003-0904-976X
Michele FilosiInstitute for Biomedicine, Eurac Research, Bolzano 39100, Italy (Affiliated institute with Lübeck University, Lübeck, Germany).ORCID 0000-0002-3872-347X
Frank MaixnerInstitute for Mummy Studies, Eurac Research, Bolzano 39100, Italy.ORCID 0000-0003-2846-8994
Christian FuchsbergerInstitute for Biomedicine, Eurac Research, Bolzano 39100, Italy (Affiliated institute with Lübeck University, Lübeck, Germany).ORCID 0000-0002-5918-8947

Funding

Design and Analysis of Human Gene Mapping StudiesR01HG009976 · NHGRI · UNIVERSITY OF MICHIGAN AT ANN ARBOR · PI BOEHNKE, MICHAEL L · 2018 to 2022
$2.5M
NHGRI NIH HHS R01 HG009976
6 · The paper itself

Abstract

Analyzing taxonomic diversity and identification in diverse ecological samples has become a crucial routine in various research and industrial fields. While DNA barcoding marker-gene approaches were once prevalent, the decreasing costs of next-generation sequencing have made metagenomic shotgun sequencing more popular and feasible. In contrast to DNA-barcoding, metagenomic shotgun sequencing offers possibilities for in-depth characterization of structural and functional diversity. However, analysis of such data is still considered a hurdle due to absence of taxa-specific databases. Here we present taxonize-gb, a command-line software tool to extract GenBank non-redundant nucleotide and protein databases, related to one or more input taxonomy identifier. Our tool allows the creation of taxa-specific reference databases tailored to specific research questions, which reduces search times and therefore represents a practical solution for researchers analyzing large metagenomic data on regular basis. Taxonize-gb is an open-source command-line Python-based tool freely available for installation at https://pypi.org/project/taxonize-gb/ and on GitHub https://github.com/msabrysarhan/taxonize_genbank. It is released under Creative Commons Attribution-NonCommercial 4.0 International License (CC BY-NC 4.0).

Identifiers

PMID38585727
PMCPMC10996545

What OpenQuestion holds

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LicenceCC BY-NC-ND
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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.